OpenAI
The Ohio State University
Stanford University
Dario AmodeiCo-founder and CEO · AnthropicResearcher↗TH
Researcher
Tom Henighan
AnthropicMember of Technical Staff
Henighan helped show that many aspects of language-model performance improve in predictable ways as training grows. He later studied where those patterns break down—including how repeated data can harm a model—and contributed to methods for making assistants more helpful and less harmful.
Career & education
Current role
Member of Technical Staff
Previously
Beehive AI2017-2019
Work and education history is primarily focused on AI-relevant roles and may not be comprehensive.
Citation Trend
Total citations to scholarly work, including research papers, technical reports, books and theses, as recorded by Google Scholar. Each point is a dated snapshot.
citations152,847As of Nov 1, '26
citations+6,121Since last snapshot, Oct 1, '26
Selected contributions
Language Models are Few-Shot Learners
With Tom Brown, Ben Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan and others ·GPT-3 performs tasks from prompts and a few examples without task-specific training.
Scaling Laws for Neural Language Models
With Jared Kaplan, Sam McCandlish, Tom Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford and others ·Measured predictable links between language-model performance, model size, data and computation.
Constitutional AI: Harmlessness from AI Feedback
With Yuntao Bai, Saurav Kadavath, Sandipan Kundu, Amanda Askell, Jackson Kernion, Andy Jones, Anna Chen and others ·Trained AI assistants to critique and improve their answers using a written set of principles.
Based on public sources. If accuracy is important, verify details using the links or references.
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Reviewed August 7, 2026 · Checked for accuracy and new information.
